Location valise diagnostic à 78160 Marly-le-roi

1. 0.0002

   SELECT cate_title_slug FROM category WHERE fami_id IN (3,5) AND cate_title_slug<>'' AND cate_title_slug IS NOT NULL

2. 0.0001

   SELECT cate_id FROM category WHERE fami_id='5' AND cate_title_slug='outillage-mecanique-automobile'

3. 0

   SELECT cate_title_slug, cate_title,cate_title_aff FROM category WHERE cate_id=227

4. 0.0001

   SELECT filtre_dptnom FROM filtredpt WHERE CONVERT(filtre_dpt USING utf8mb4) COLLATE utf8mb4_general_ci = CONVERT('78' USING utf8mb4) COLLATE utf8mb4_general_ci

5. 0.0001

   SELECT ville_nom FROM villes WHERE ville_cp='78160' AND ville_nom like '%marly%le%roi%' ORDER BY ville_population_2012 DESC LIMIT 0,1

6. 0.0005

   SELECT DISTINCT ssrubr_slug FROM ssrubr WHERE ssrubr_visu=1 AND fami_id IN (3,5) AND ssrubr_slug IS NOT NULL AND ssrubr_slug<>''

7. 0.0001

   SELECT ssrubr_id, ssrubr_keywords, ssrubr_title, ssrubr_slug, ssrubr_mail, ssrubr_photo FROM ssrubr WHERE (ssrubr_keywords like '%valise%diag%auto%' OR ssrubr_title like '%valise%diag%auto%' OR ssrubr_slug like '%valise%diag%auto%') AND cate_id='227' ORDER BY ssrubr_id LIMIT 0,1

8. 0.0001

   SHOW TABLES LIKE 'pays'

9. 0.0002

   SHOW COLUMNS FROM pays LIKE 'pays_tel_%'

10. 0.0002

    SELECT pays_code, pays_nom, pays_actif, pays_NDD, pays_drapeau, pays_lang, pays_tel, pays_nb_annonces, pays_tel_masque, pays_tel_max, pays_tel_fmt_paires, pays_tel_mode FROM pays ORDER BY pays_nom ASC

11. 0.0001

    SELECT ville_cp, ville_latitude_deg,ville_longitude_deg FROM villes v WHERE ville_cp='78160'

12. 0.002

    SELECT ville_cp, ROUND((((acos(sin((48.8667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.8667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.08333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.686835678816 AND ville_latitude_deg<49.046564321184 AND ville_longitude_deg>1.8099018543365 AND ville_longitude_deg<2.3567581456635 HAVING distance <= 20 ORDER BY distance ASC

13. 0.0001

    SELECT keywords_id FROM ssrubr_keywords WHERE keywords_title='valise diagnostique; valise diag auto; valise diag'

14. 0.0021

    SELECT count(wish_id) as nbwish FROM wish WHERE fami_id='5' AND cate_id='227' AND ssrubr_id='874' AND wish_visu IN (1,6,10) AND wish_cp like '78160%'

15. 0.0001

    SELECT * FROM texte WHERE cate_id=227

16. 0.0002

    SELECT ssrubr_texte_haut FROM ssrubr WHERE fami_id='5' AND (ssrubr_keywords='valise diagnostique; valise diag auto; valise diag' OR ssrubr_slug='valise-diagnostique;-valise-diag-auto;-valise-diag' OR (ssrubr_title like '%valise diagnostique; valise diag auto; valise diag%')) AND cate_id='227' ORDER BY ssrubr_id LIMIT 0,1

17. 0.0001

    SELECT ssrubr_texte_haut, ssrubr_texte_bas FROM ssrubr WHERE ssrubr_slug='valise-diag-auto' AND cate_id='227'

18. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='78160'

19. 0.002

    SELECT ville_cp, ROUND((((acos(sin((48.8667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.8667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.08333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.686835678816 AND ville_latitude_deg<49.046564321184 AND ville_longitude_deg>1.8099018543365 AND ville_longitude_deg<2.3567581456635 HAVING distance <= 20 ORDER BY distance ASC

20. 0.0073

    SELECT ville_cp, ROUND((((acos(sin((48.8667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.8667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.08333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.417039197041 AND ville_latitude_deg<49.316360802959 AND ville_longitude_deg>1.3997537413096 AND ville_longitude_deg<2.7669062586904 HAVING distance <= 50 ORDER BY distance ASC

21. 0.0022

    SELECT wish.*, ui.util_photo, ui.util_prenom, ui.util_nom, ui.stripe_account_id, ui.util_verify, ville_cp,ville_nom,ville_latitude_deg,ville_longitude_deg, ROUND((((acos(sin((48.8667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.8667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.08333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM wish LEFT JOIN util_info ui ON wish.util_id=ui.util_id LEFT JOIN villes v ON wish.wish_cp=v.ville_cp WHERE wish_id IS NOT NULL AND fami_id='5' AND cate_id='227' AND ssrubr_id='874' AND wish_visu IN (1,6,10) AND wish_cp IN (78160,78160,78620,78750,78870,78112,78590,78430,78560,78380,78290,78100,78230,78110,78150,78590,78240,78400,78170,78860,78150,78330,78240,78450,78360,78210,78450,92430,92420,78300,92380,78000,78600,78810,92500,78390,78630,92410,78420,78340,92000,78220,78955,92210,78800,92310,78140,78600,92800,92150,78810,78670,78670,78190,78121,78260,78280,78370,92370,78180,78530,78350,78500,95870,78850,78350,92250,92100,92400,78570,78700,78960,78117,78630,92190,92360,78540,95530,78580,92700,78990,78570,92200,78640,78510,92270,92130,78640,78780,78114,78480,78117,95370,78470,92300,78580,95100,78920,92140,95240,92600,78130,78470,78640,78124,78650,95220,91400,91570,78320,92110,78124,92170,92350,78760,92320,95110,78310,95000,95610,92240,78640,91190,95130,95280,91190,91430,78320,92260,92330,78410,92290,92230,78580,92220,95000,95480,91430,78310,78580,92120,95180,95218,95210,78490,95130,78470,95000,78126,95120,93400,78650,91370,78460,95250,78740,93800,95490,75012,75000,75002,75003,75005,75004,75011,75014,75017,75018,75015,75006,75019,75020,75007,75009,75008,75010,75016,75013,75001,75116,94250,78490,78130,78740,78320,78410,78490,78490,95800,78770,78720,78720,91440,78690,78770,92390,93450,94110,78770,92340,91400,78250) AND type_id=1 GROUP BY wish_id

22. 0.0001

    SELECT util_id, util_photo, util_prenom, util_nom, stripe_account_id, util_verify FROM util_info WHERE util_id IN (205061,279594,279641,334923,454800)

23. 0.0002

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 205061 AND W.type_id = 1) OR (W.util_id <> 205061 AND W.type_id = 2)) AND (M.post_util_id = 205061 OR M.dest_util_id = 205061) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

24. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=205061 AND note_visu IN (1,3,4)

25. 0.0002

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 279594 AND W.type_id = 1) OR (W.util_id <> 279594 AND W.type_id = 2)) AND (M.post_util_id = 279594 OR M.dest_util_id = 279594) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

26. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=279594 AND note_visu IN (1,3,4)

27. 0.0001

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 279641 AND W.type_id = 1) OR (W.util_id <> 279641 AND W.type_id = 2)) AND (M.post_util_id = 279641 OR M.dest_util_id = 279641) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

28. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=279641 AND note_visu IN (1,3,4)

29. 0.0001

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 334923 AND W.type_id = 1) OR (W.util_id <> 334923 AND W.type_id = 2)) AND (M.post_util_id = 334923 OR M.dest_util_id = 334923) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

30. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=334923 AND note_visu IN (1,3,4)

31. 0.0001

    SELECT COALESCE(SUM(CASE WHEN M.match_step <> 3 THEN 1 ELSE 0 END), 0) AS h, COALESCE(SUM(CASE WHEN M.match_step = 3 THEN 1 ELSE 0 END), 0) AS cancelled FROM `match` AS M INNER JOIN wish AS W ON W.wish_id = M.wish_id WHERE ((W.util_id = 454800 AND W.type_id = 1) OR (W.util_id <> 454800 AND W.type_id = 2)) AND (M.post_util_id = 454800 OR M.dest_util_id = 454800) AND M.buy_stripe_pi_id IS NOT NULL AND M.buy_stripe_pi_id <> ''

32. 0.0001

    SELECT ROUND(AVG(note), 1) AS note_moy, COUNT(note) AS nb_avis FROM `note` WHERE dest_util_id=454800 AND note_visu IN (1,3,4)

33. 0.0001

    SELECT ville_cp, ville_latitude_deg, ville_longitude_deg FROM villes v WHERE ville_cp='78160'

34. 0.0022

    SELECT ville_cp, ROUND((((acos(sin((48.8667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.8667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.08333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.686835678816 AND ville_latitude_deg<49.046564321184 AND ville_longitude_deg>1.8099018543365 AND ville_longitude_deg<2.3567581456635 HAVING distance <= 20 ORDER BY distance ASC

35. 0.0076

    SELECT ville_cp, ROUND((((acos(sin((48.8667*pi()/180)) * sin((ville_latitude_deg*pi()/180))+cos((48.8667*pi()/180)) * cos((ville_latitude_deg*pi()/180)) * cos(((2.08333- ville_longitude_deg)* pi()/180))))*180/pi())*60*1.1515* 1.609344),2) as distance FROM villes WHERE ville_latitude_deg>48.417039197041 AND ville_latitude_deg<49.316360802959 AND ville_longitude_deg>1.3997537413096 AND ville_longitude_deg<2.7669062586904 HAVING distance <= 50 ORDER BY distance ASC

36. 0.0001

    SELECT ssr.ssrubr_id, ssr.ssrubr_slug, ssr.ssrubr_mail, ssr.ssrubr_mail_bis, ssr.ssrubr_keywords, ssr.ssrubr_bt2, ssr.ssrubr_photo, c.cate_title_slug, f.fami_url FROM ssrubr ssr, category c, family f WHERE ssr.cate_id=c.cate_id AND c.fami_id=f.fami_id AND ssr.ssrubr_id IN (874)

37. 0.0002

    SELECT util_id FROM util_abo WHERE abo_type=4 AND abo_actif=1 AND abo_expire>SYSDATE() AND util_id IN (279594,454800,205061,334923,279641)

38. 0.0001

    SELECT util_id, util_photo FROM util_info WHERE util_id IN (279594,454800,205061,334923,279641)

39. 0.0002

    SELECT ss.fami_id, fami_url, ss.cate_id, cate_title_slug, keywords_title FROM `ssrubr_keywords` sk, ssrubr ss, category c, family f WHERE sk.ssrubr_id=ss.ssrubr_id AND ss.cate_id=c.cate_id AND c.fami_id=f.fami_id AND (ssrubr_slug='valise diagnostique; valise diag auto; valise diag' OR ssrubr_slug like '%valise diagnostique; valise diag auto; valise diag%' OR MATCH (ssrubr_slug) AGAINST ('(+valise +diagnostique; +valise +diag +auto; +valise +diag)')) AND sk.ssrubr_id='874' AND keywords_visu=1 ORDER BY keywords_nb DESC, keywords_id ASC LIMIT 0,10

40. 0.0003

    SELECT ss.ssrubr_id, ss.ssrubr_slug, ss.ssrubr_title, ss.ssrubr_keywords, ss.ssrubr_mail, c.cate_title_slug FROM ssrubr ss INNER JOIN category c ON ss.cate_id = c.cate_id WHERE ss.ssrubr_visu = 1 AND ss.fami_id = 5 AND ss.cate_id = 227 AND ss.ssrubr_id <> 874 ORDER BY ss.ssrubr_order ASC, ss.ssrubr_id ASC LIMIT 10

41. 0.0001

    SELECT * FROM actu WHERE ssrubr_id='874' AND actu_niveau=0 ORDER BY actu_ordre DESC

42. 0.0001

    SELECT fami_id as id, fami_title as title, fami_tutotitle, fami_tutodesc, fami_buttontitle, fami_url as slug FROM `family`

43. 0.0001

    SELECT cate_id as id, cate_title as title, cate_title_slug as slug, fami_id FROM `category` WHERE cate_visu=1 AND fami_id='5' AND cate_cate_id IS NULL ORDER BY cate_order ASC

44. 0.0002

    SELECT ssrubr_id AS id, ssrubr_title as title, ssrubr_slug as slug, ssrubr_photo, cate_id, fami_id FROM ssrubr WHERE ssrubr_visu=1 AND cate_id IN (227) ORDER BY ssrubr_order ASC

45. 0.0009

    SELECT AVG(note) as note_moy FROM note WHERE note_visu IN (1,2,3,4) AND post_util_id<>7

46. 0.0239

    SELECT COUNT(*) AS nbavis FROM note n INNER JOIN util_info dest ON n.dest_util_id=dest.util_id INNER JOIN util_info post ON n.post_util_id=post.util_id INNER JOIN wish w ON n.wish_id=w.wish_id WHERE n.note_visu IN (1,2,3,4) AND n.post_util_id<>'7'

47. 0.0169

    SELECT count(*) as nbwish FROM wish WHERE wish_visu IN (1,6,10)

47 requetes sql en 0.0722